Machine Learning & Deep Learning Projects For Beginners 2023

欢迎来到本课程，  “2023 年初学者机器学习和深度学习项目”。

在本课程中，我将教您处理 23 个不同的项目，这些项目来自不同的类别，例如回归、分类、聚类、ANN、CNN、RNN 和迁移学习！

人工智能和机器学习在当今世界呈指数级增长。AI 和深度学习有多种应用，如 自动驾驶汽车、聊天机器人、图像识别、虚拟辅助、ALEXA 等……

通过本课程，您将以简单的方式了解机器学习和深度学习的复杂性，因为我们将使用 Google colab Notebook。

在 Google Colab 中 ，无论您是专家还是初学者， 您都可以从零安装 开始编码，在本课程中，您将学习机器学习和深度学习算法的端到端实现。

您将从事的项目清单，

项目一：乳腺癌检测

项目二：客户流失率预测

项目三：医疗保险保费预测

项目四：房价预测

项目五：基于财务数据的客户电子签约

项目六：信用卡欺诈检测

项目七：员工流失预测

项目 8：客户细分

项目九：二手车价格预测

项目十：餐厅点评分类

项目 11：使用 ANN 进行多类图像分类

项目 12：使用 ANN 进行二进制数据分类

项目 13：使用 CNN 进行图像中的对象识别

项目 14：使用 CNN 进行二值图像分类

项目 15：使用 CNN 进行数字识别

项目 16：使用 CNN 检测乳腺癌

项目 17：使用 CNN 预测银行客户满意度

项目 18：使用 CNN 进行信用卡欺诈检测

项目 19：使用 RNN – LSTM 进行 IMDB 审查分类

项目 20：使用 RNN – LSTM 进行多类图像分类

项目 21：使用 RNN 和 LSTM 进行谷歌股票价格预测

项目 22：猫狗分类的迁移学习

项目 23：使用 NLTK 进行电影评论分类

通过本课程，我将教您：

1) 从事机器学习中的回归、分类和聚类项目

2）机器学习中的文本项目

3) NN、CNN、RNN 和迁移学习项目

4）从头开始构建神经网络

5) 你将对人工神经网络、卷积神经网络和递归神经网络有完整的理解

3) 您将学习使用 LSTM 和 GRU 构建神经网络

4) 动手迁移学习

5) 通过做一个文本分类项目来学习自然语言处理

Work On 23 Projects in Machine Learning & Deep Learning, Regression, Classification, Clustering, ANN, CNN, RNN, & More!

Published 11/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 7.82 GB | Duration: 18h 45m

What you’ll learn

Complete understanding of Machine Learning Project flow
Machine Learning and Deep Learning Practical Applications
Machine Learning for Regression Problems
Machine Learning for Classification Problems
Clustering with Machine Learning
NLP with Machine Learning
Improving the performance of a machine learning model
Projects on Artificial Neural Network (ANN)
Projects on Convolutional Neural Network (CNN)
Projects on Recurrent Neural Network (RNN)
Projects on Transfer Learning

Requirements

Python Programming Basics
Basic understanding of Machine Learning and Deep Learning

Description

Welcome to this course, ‘Machine Learning & Deep Learning Projects for Beginners 2023’.

In this course, I will teach you to work on different 23 projects, which are from various categories like Regression, Classification, Clustering, ANN, CNN, RNN, and Transfer Learning!

Artificial Intelligence and Machine Learning are growing exponentially in today’s world. There is multiple application of AI and Deep Learning like Self Driving Cars, Chatbots, Image Recognition, Virtual Assistance, ALEXA, and so on…

With this course, you will understand the complexities of Machine Learning and Deep Learning in an easy way, as we will be working with Google colab Notebook.

In Google Colab you can start the coding with Zero Installation, whether you’re an expert or a beginner, in this course you will learn an end-to-end implementation of Machine Learning and Deep Learning Algorithms.

List of the Projects that you will work on,

Project 1: Breast Cancer Detection

Project 2: Customer churn rate prediction

Project 3: Medical insurance premium prediction

Project 4: House price prediction

Project 5: E signing of customers based on financial data

Project 6: Credit card fraud detection

Project 7: Employee Attrition Prediction

Project 8:  Customer Segmentation

Project 9: Used Car Price Prediction

Project 10: Restaurant Reviews Classification

Project 11: Multiclass image classification with ANN

Project 12: Binary Data Classification with ANN

Project 13: Object Recognition in Images with CNN

Project 14: Binary Image Classification with CNN

Project 15: Digit Recognition with CNN

Project 16: Breast Cancer Detection with CNN

Project 17: Predicting the Bank Customer Satisfaction with CNN

Project 18: Credit Card Fraud Detection with CNN

Project 19: IMDB Review Classification with RNN – LSTM

Project 20: Multiclass Image Classification with RNN – LSTM

Project 21: Google Stock Price Prediction with RNN and LSTM

Project 22: Transfer Learning for Cats and Dogs Classification

Project 23: Movie Review Classification with NLTK

With this course, I will teach you:

1) To work on Regression, Classification, and Clustering Projects in Machine Learning

2) Text projects in Machine Learning

3) NN, CNN, RNN, and Transfer Learning Projects

4) To build the Neural Networks from the scratch

5) You will have a complete understanding of Artificial Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks

3) You will learn to build the neural networks with LSTM and GRU

4) Hands-On Transfer Learning

5) Learn Natural Language Processing by doing a text classification project

So what are you waiting for, Enroll Now and learn Machine Learning and Deep Learning to advance your career and increase your knowledge!

Regards,

Vijay Gadhave